Package evaluation of SDeMo on Julia 1.13.0-DEV.1035 (d28a587c89*) started at 2025-08-24T16:31:46.788


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.43s


################################################################################
# Installation
#

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [3e5feb82] + SDeMo v1.5.2
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.19.0
  [31c24e10] + Distributions v0.25.120
  [ffbed154] + DocStringExtensions v0.9.5
  [1a297f60] + FillArrays v1.13.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [92d709cd] + IrrationalConstants v0.2.4
  [692b3bcd] + JLLWrappers v1.7.1
  [682c06a0] + JSON v0.21.4
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [e1d29d7a] + Missings v1.2.0
  [6f286f6a] + MultivariateStats v0.10.3
  [bac558e1] + OrderedCollections v1.8.1
  [90014a1f] + PDMats v0.11.35
  [69de0a69] + Parsers v2.8.3
  [aea7be01] + PrecompileTools v1.3.2
  [21216c6a] + Preferences v1.5.0
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.8.0
  [3e5feb82] + SDeMo v1.5.2
  [a2af1166] + SortingAlgorithms v1.2.2
  [276daf66] + SpecialFunctions v2.5.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.7.1
  [2913bbd2] + StatsBase v0.34.6
  [4c63d2b9] + StatsFuns v1.5.0
  [1c621080] + TestItems v1.0.0
⌅ [68821587] + Arpack_jll v3.5.1+1
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [0dad84c5] + ArgTools v1.1.2
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [f43a241f] + Downloads v1.7.0
  [7b1f6079] + FileWatching v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0
  [b27032c2] + LibCURL v0.6.4
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.3.0
  [44cfe95a] + Pkg v1.13.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.11.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [a4e569a6] + Tar v1.10.0
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] + LibCURL_jll v8.15.0+1
  [e37daf67] + LibGit2_jll v1.9.1+0
  [29816b5a] + LibSSH2_jll v1.11.3+1
  [14a3606d] + MozillaCACerts_jll v2025.8.12
  [4536629a] + OpenBLAS_jll v0.3.29+0
  [05823500] + OpenLibm_jll v0.8.7+0
  [458c3c95] + OpenSSL_jll v3.5.2+0
  [efcefdf7] + PCRE2_jll v10.45.0+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [83775a58] + Zlib_jll v1.3.1+2
  [3161d3a3] + Zstd_jll v1.5.7+1
  [8e850b90] + libblastrampoline_jll v5.13.1+0
  [8e850ede] + nghttp2_jll v1.66.0+0
  [3f19e933] + p7zip_jll v17.6.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 5.08s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 35.0s


################################################################################
# Testing
#

     Testing SDeMo
      Status `/tmp/jl_vWgcS0/Project.toml`
  [3e5feb82] SDeMo v1.5.2
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_vWgcS0/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.0
  [31c24e10] Distributions v0.25.120
  [ffbed154] DocStringExtensions v0.9.5
  [1a297f60] FillArrays v1.13.0
  [34004b35] HypergeometricFunctions v0.3.28
  [92d709cd] IrrationalConstants v0.2.4
  [692b3bcd] JLLWrappers v1.7.1
  [682c06a0] JSON v0.21.4
  [2ab3a3ac] LogExpFunctions v0.3.29
  [e1d29d7a] Missings v1.2.0
  [6f286f6a] MultivariateStats v0.10.3
  [bac558e1] OrderedCollections v1.8.1
  [90014a1f] PDMats v0.11.35
  [69de0a69] Parsers v2.8.3
  [aea7be01] PrecompileTools v1.3.2
  [21216c6a] Preferences v1.5.0
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.8.0
  [3e5feb82] SDeMo v1.5.2
  [a2af1166] SortingAlgorithms v1.2.2
  [276daf66] SpecialFunctions v2.5.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.6
  [4c63d2b9] StatsFuns v1.5.0
  [f8b46487] TestItemRunner v1.1.0
  [1c621080] TestItems v1.0.0
⌅ [68821587] Arpack_jll v3.5.1+1
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.13.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.15.0+1
  [e37daf67] LibGit2_jll v1.9.1+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.8.12
  [4536629a] OpenBLAS_jll v0.3.29+0
  [05823500] OpenLibm_jll v0.8.7+0
  [458c3c95] OpenSSL_jll v3.5.2+0
  [efcefdf7] PCRE2_jll v10.45.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.13.1+0
  [8e850ede] nghttp2_jll v1.66.0+0
  [3f19e933] p7zip_jll v17.6.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.546
[ Info: [ 4 vars.] MCC val. ≈ 0.553
[ Info: Optimal var. pool: [1, 12, 16, 17]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.759
[ Info: [ 2 vars.] MCC val. ≈ 0.787
[ Info: [ 3 vars.] MCC val. ≈ 0.8
[ Info: Optimal var. pool: [8, 15, 6]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.529
[ Info: [17 vars.] MCC val. ≈ 0.752
[ Info: [16 vars.] MCC val. ≈ 0.759
[ Info: [15 vars.] MCC val. ≈ 0.765
[ Info: Optimal var. pool: [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.89
[ Info: [ 7 vars.] MCC val. ≈ 0.897
[ Info: Optimal var. pool: [1, 2, 3, 6, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.485
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.807
[ Info: [ 2 vars.] MCC val. ≈ 0.862
[ Info: Optimal var. pool: [5, 8]
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7307
[ Info: Optimal 2 variables model - mcc ≈ 0.7698
[ Info: Optimal 3 variables model - mcc ≈ 0.7794
[ Info: Returning model with 3 variables - mcc ≈ 0.7794
[ Info: [  0%] LOSS: training ≈ 0.4909 validation ≈ 0.4979 (101%)
[ Info: [  1%] LOSS: training ≈ 0.4173 validation ≈ 0.4343 (104%)
[ Info: [  2%] LOSS: training ≈ 0.3815 validation ≈ 0.4025 (106%)
[ Info: [  2%] LOSS: training ≈ 0.3603 validation ≈ 0.3835 (106%)
[ Info: [  2%] LOSS: training ≈ 0.3462 validation ≈ 0.3707 (107%)
[ Info: [  3%] LOSS: training ≈ 0.336  validation ≈ 0.3615 (108%)
[ Info: [  4%] LOSS: training ≈ 0.3282 validation ≈ 0.3543 (108%)
[ Info: [  4%] LOSS: training ≈ 0.3219 validation ≈ 0.3486 (108%)
[ Info: [  4%] LOSS: training ≈ 0.3167 validation ≈ 0.3439 (109%)
[ Info: [  5%] LOSS: training ≈ 0.3123 validation ≈ 0.3399 (109%)
[ Info: [  6%] LOSS: training ≈ 0.3085 validation ≈ 0.3365 (109%)
[ Info: [  6%] LOSS: training ≈ 0.3051 validation ≈ 0.3334 (109%)
[ Info: [  6%] LOSS: training ≈ 0.3021 validation ≈ 0.3308 (110%)
[ Info: [  7%] LOSS: training ≈ 0.2993 validation ≈ 0.3284 (110%)
[ Info: [  8%] LOSS: training ≈ 0.2969 validation ≈ 0.3263 (110%)
[ Info: [  8%] LOSS: training ≈ 0.2946 validation ≈ 0.3243 (110%)
[ Info: [  8%] LOSS: training ≈ 0.2925 validation ≈ 0.3226 (110%)
[ Info: [  9%] LOSS: training ≈ 0.2906 validation ≈ 0.3209 (110%)
[ Info: [ 10%] LOSS: training ≈ 0.2888 validation ≈ 0.3194 (111%)
[ Info: [ 10%] LOSS: training ≈ 0.2871 validation ≈ 0.318  (111%)
[ Info: [ 10%] LOSS: training ≈ 0.2855 validation ≈ 0.3168 (111%)
[ Info: [ 11%] LOSS: training ≈ 0.284  validation ≈ 0.3155 (111%)
[ Info: [ 12%] LOSS: training ≈ 0.2826 validation ≈ 0.3144 (111%)
[ Info: [ 12%] LOSS: training ≈ 0.2813 validation ≈ 0.3134 (111%)
[ Info: [ 12%] LOSS: training ≈ 0.2801 validation ≈ 0.3124 (112%)
[ Info: [ 13%] LOSS: training ≈ 0.2789 validation ≈ 0.3115 (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2778 validation ≈ 0.3106 (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2767 validation ≈ 0.3097 (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2757 validation ≈ 0.309  (112%)
[ Info: [ 15%] LOSS: training ≈ 0.2747 validation ≈ 0.3082 (112%)
[ Info: [ 16%] LOSS: training ≈ 0.2738 validation ≈ 0.3075 (112%)
[ Info: [ 16%] LOSS: training ≈ 0.2729 validation ≈ 0.3068 (112%)
[ Info: [ 16%] LOSS: training ≈ 0.272  validation ≈ 0.3062 (113%)
[ Info: [ 17%] LOSS: training ≈ 0.2712 validation ≈ 0.3056 (113%)
[ Info: [ 18%] LOSS: training ≈ 0.2704 validation ≈ 0.305  (113%)
[ Info: [ 18%] LOSS: training ≈ 0.2696 validation ≈ 0.3044 (113%)
[ Info: [ 18%] LOSS: training ≈ 0.2689 validation ≈ 0.3039 (113%)
[ Info: [ 19%] LOSS: training ≈ 0.2682 validation ≈ 0.3034 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2675 validation ≈ 0.3029 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2669 validation ≈ 0.3025 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2663 validation ≈ 0.302  (113%)
[ Info: [ 21%] LOSS: training ≈ 0.2657 validation ≈ 0.3016 (114%)
[ Info: [ 22%] LOSS: training ≈ 0.2651 validation ≈ 0.3012 (114%)
[ Info: [ 22%] LOSS: training ≈ 0.2645 validation ≈ 0.3008 (114%)
[ Info: [ 22%] LOSS: training ≈ 0.264  validation ≈ 0.3004 (114%)
[ Info: [ 23%] LOSS: training ≈ 0.2635 validation ≈ 0.3    (114%)
[ Info: [ 24%] LOSS: training ≈ 0.263  validation ≈ 0.2997 (114%)
[ Info: [ 24%] LOSS: training ≈ 0.2625 validation ≈ 0.2994 (114%)
[ Info: [ 24%] LOSS: training ≈ 0.262  validation ≈ 0.299  (114%)
[ Info: [ 25%] LOSS: training ≈ 0.2615 validation ≈ 0.2987 (114%)
[ Info: [ 26%] LOSS: training ≈ 0.2611 validation ≈ 0.2984 (114%)
[ Info: [ 26%] LOSS: training ≈ 0.2607 validation ≈ 0.2982 (114%)
[ Info: [ 26%] LOSS: training ≈ 0.2603 validation ≈ 0.2979 (114%)
[ Info: [ 27%] LOSS: training ≈ 0.2599 validation ≈ 0.2976 (115%)
[ Info: [ 28%] LOSS: training ≈ 0.2595 validation ≈ 0.2974 (115%)
[ Info: [ 28%] LOSS: training ≈ 0.2591 validation ≈ 0.2971 (115%)
[ Info: [ 28%] LOSS: training ≈ 0.2587 validation ≈ 0.2969 (115%)
[ Info: [ 29%] LOSS: training ≈ 0.2584 validation ≈ 0.2967 (115%)
[ Info: [ 30%] LOSS: training ≈ 0.258  validation ≈ 0.2964 (115%)
[ Info: [ 30%] LOSS: training ≈ 0.2577 validation ≈ 0.2962 (115%)
[ Info: [ 30%] LOSS: training ≈ 0.2574 validation ≈ 0.296  (115%)
[ Info: [ 31%] LOSS: training ≈ 0.2571 validation ≈ 0.2958 (115%)
[ Info: [ 32%] LOSS: training ≈ 0.2568 validation ≈ 0.2956 (115%)
[ Info: [ 32%] LOSS: training ≈ 0.2565 validation ≈ 0.2955 (115%)
[ Info: [ 32%] LOSS: training ≈ 0.2562 validation ≈ 0.2953 (115%)
[ Info: [ 33%] LOSS: training ≈ 0.2559 validation ≈ 0.2951 (115%)
[ Info: [ 34%] LOSS: training ≈ 0.2556 validation ≈ 0.2949 (115%)
[ Info: [ 34%] LOSS: training ≈ 0.2554 validation ≈ 0.2948 (115%)
[ Info: [ 34%] LOSS: training ≈ 0.2551 validation ≈ 0.2946 (115%)
[ Info: [ 35%] LOSS: training ≈ 0.2549 validation ≈ 0.2945 (116%)
[ Info: [ 36%] LOSS: training ≈ 0.2546 validation ≈ 0.2943 (116%)
[ Info: [ 36%] LOSS: training ≈ 0.2544 validation ≈ 0.2942 (116%)
[ Info: [ 36%] LOSS: training ≈ 0.2541 validation ≈ 0.2941 (116%)
[ Info: [ 37%] LOSS: training ≈ 0.2539 validation ≈ 0.2939 (116%)
[ Info: [ 38%] LOSS: training ≈ 0.2537 validation ≈ 0.2938 (116%)
[ Info: [ 38%] LOSS: training ≈ 0.2535 validation ≈ 0.2937 (116%)
[ Info: [ 38%] LOSS: training ≈ 0.2533 validation ≈ 0.2936 (116%)
[ Info: [ 39%] LOSS: training ≈ 0.2531 validation ≈ 0.2935 (116%)
[ Info: [ 40%] LOSS: training ≈ 0.2529 validation ≈ 0.2934 (116%)
[ Info: [ 40%] LOSS: training ≈ 0.2527 validation ≈ 0.2933 (116%)
[ Info: [ 40%] LOSS: training ≈ 0.2525 validation ≈ 0.2932 (116%)
[ Info: [ 41%] LOSS: training ≈ 0.2523 validation ≈ 0.2931 (116%)
[ Info: [ 42%] LOSS: training ≈ 0.2522 validation ≈ 0.293  (116%)
[ Info: [ 42%] LOSS: training ≈ 0.252  validation ≈ 0.2929 (116%)
[ Info: [ 42%] LOSS: training ≈ 0.2518 validation ≈ 0.2928 (116%)
[ Info: [ 43%] LOSS: training ≈ 0.2517 validation ≈ 0.2927 (116%)
[ Info: [ 44%] LOSS: training ≈ 0.2515 validation ≈ 0.2926 (116%)
[ Info: [ 44%] LOSS: training ≈ 0.2514 validation ≈ 0.2926 (116%)
[ Info: [ 44%] LOSS: training ≈ 0.2512 validation ≈ 0.2925 (116%)
[ Info: [ 45%] LOSS: training ≈ 0.2511 validation ≈ 0.2924 (116%)
[ Info: [ 46%] LOSS: training ≈ 0.2509 validation ≈ 0.2923 (117%)
[ Info: [ 46%] LOSS: training ≈ 0.2508 validation ≈ 0.2923 (117%)
[ Info: [ 46%] LOSS: training ≈ 0.2506 validation ≈ 0.2922 (117%)
[ Info: [ 47%] LOSS: training ≈ 0.2505 validation ≈ 0.2921 (117%)
[ Info: [ 48%] LOSS: training ≈ 0.2504 validation ≈ 0.2921 (117%)
[ Info: [ 48%] LOSS: training ≈ 0.2502 validation ≈ 0.292  (117%)
[ Info: [ 48%] LOSS: training ≈ 0.2501 validation ≈ 0.292  (117%)
[ Info: [ 49%] LOSS: training ≈ 0.25   validation ≈ 0.2919 (117%)
[ Info: [ 50%] LOSS: training ≈ 0.2499 validation ≈ 0.2918 (117%)
[ Info: [ 50%] LOSS: training ≈ 0.2498 validation ≈ 0.2918 (117%)
[ Info: [ 50%] LOSS: training ≈ 0.2496 validation ≈ 0.2917 (117%)
[ Info: [ 51%] LOSS: training ≈ 0.2495 validation ≈ 0.2917 (117%)
[ Info: [ 52%] LOSS: training ≈ 0.2494 validation ≈ 0.2916 (117%)
[ Info: [ 52%] LOSS: training ≈ 0.2493 validation ≈ 0.2916 (117%)
[ Info: [ 52%] LOSS: training ≈ 0.2492 validation ≈ 0.2916 (117%)
[ Info: [ 53%] LOSS: training ≈ 0.2491 validation ≈ 0.2915 (117%)
[ Info: [ 54%] LOSS: training ≈ 0.249  validation ≈ 0.2915 (117%)
[ Info: [ 54%] LOSS: training ≈ 0.2489 validation ≈ 0.2914 (117%)
[ Info: [ 55%] LOSS: training ≈ 0.2488 validation ≈ 0.2914 (117%)
[ Info: [ 55%] LOSS: training ≈ 0.2487 validation ≈ 0.2914 (117%)
[ Info: [ 56%] LOSS: training ≈ 0.2486 validation ≈ 0.2913 (117%)
[ Info: [ 56%] LOSS: training ≈ 0.2486 validation ≈ 0.2913 (117%)
[ Info: [ 56%] LOSS: training ≈ 0.2485 validation ≈ 0.2912 (117%)
[ Info: [ 57%] LOSS: training ≈ 0.2484 validation ≈ 0.2912 (117%)
[ Info: [ 57%] LOSS: training ≈ 0.2483 validation ≈ 0.2912 (117%)
[ Info: [ 58%] LOSS: training ≈ 0.2482 validation ≈ 0.2912 (117%)
[ Info: [ 58%] LOSS: training ≈ 0.2481 validation ≈ 0.2911 (117%)
[ Info: [ 59%] LOSS: training ≈ 0.2481 validation ≈ 0.2911 (117%)
[ Info: [ 60%] LOSS: training ≈ 0.248  validation ≈ 0.2911 (117%)
[ Info: [ 60%] LOSS: training ≈ 0.2479 validation ≈ 0.291  (117%)
[ Info: [ 60%] LOSS: training ≈ 0.2478 validation ≈ 0.291  (117%)
[ Info: [ 61%] LOSS: training ≈ 0.2478 validation ≈ 0.291  (117%)
[ Info: [ 62%] LOSS: training ≈ 0.2477 validation ≈ 0.291  (117%)
[ Info: [ 62%] LOSS: training ≈ 0.2476 validation ≈ 0.2909 (117%)
[ Info: [ 62%] LOSS: training ≈ 0.2476 validation ≈ 0.2909 (118%)
[ Info: [ 63%] LOSS: training ≈ 0.2475 validation ≈ 0.2909 (118%)
[ Info: [ 64%] LOSS: training ≈ 0.2474 validation ≈ 0.2909 (118%)
[ Info: [ 64%] LOSS: training ≈ 0.2474 validation ≈ 0.2909 (118%)
[ Info: [ 64%] LOSS: training ≈ 0.2473 validation ≈ 0.2908 (118%)
[ Info: [ 65%] LOSS: training ≈ 0.2472 validation ≈ 0.2908 (118%)
[ Info: [ 66%] LOSS: training ≈ 0.2472 validation ≈ 0.2908 (118%)
[ Info: [ 66%] LOSS: training ≈ 0.2471 validation ≈ 0.2908 (118%)
[ Info: [ 66%] LOSS: training ≈ 0.2471 validation ≈ 0.2908 (118%)
[ Info: [ 67%] LOSS: training ≈ 0.247  validation ≈ 0.2908 (118%)
[ Info: [ 68%] LOSS: training ≈ 0.2469 validation ≈ 0.2907 (118%)
[ Info: [ 68%] LOSS: training ≈ 0.2469 validation ≈ 0.2907 (118%)
[ Info: [ 68%] LOSS: training ≈ 0.2468 validation ≈ 0.2907 (118%)
[ Info: [ 69%] LOSS: training ≈ 0.2468 validation ≈ 0.2907 (118%)
[ Info: [ 70%] LOSS: training ≈ 0.2467 validation ≈ 0.2907 (118%)
[ Info: [ 70%] LOSS: training ≈ 0.2467 validation ≈ 0.2907 (118%)
[ Info: [ 70%] LOSS: training ≈ 0.2466 validation ≈ 0.2907 (118%)
[ Info: [ 71%] LOSS: training ≈ 0.2466 validation ≈ 0.2907 (118%)
[ Info: [ 72%] LOSS: training ≈ 0.2465 validation ≈ 0.2906 (118%)
[ Info: [ 72%] LOSS: training ≈ 0.2465 validation ≈ 0.2906 (118%)
[ Info: [ 72%] LOSS: training ≈ 0.2464 validation ≈ 0.2906 (118%)
[ Info: [ 73%] LOSS: training ≈ 0.2464 validation ≈ 0.2906 (118%)
[ Info: [ 74%] LOSS: training ≈ 0.2464 validation ≈ 0.2906 (118%)
[ Info: [ 74%] LOSS: training ≈ 0.2463 validation ≈ 0.2906 (118%)
[ Info: [ 74%] LOSS: training ≈ 0.2463 validation ≈ 0.2906 (118%)
[ Info: [ 75%] LOSS: training ≈ 0.2462 validation ≈ 0.2906 (118%)
[ Info: [ 76%] LOSS: training ≈ 0.2462 validation ≈ 0.2906 (118%)
[ Info: [ 76%] LOSS: training ≈ 0.2461 validation ≈ 0.2906 (118%)
[ Info: [ 76%] LOSS: training ≈ 0.2461 validation ≈ 0.2906 (118%)
[ Info: [ 77%] LOSS: training ≈ 0.2461 validation ≈ 0.2906 (118%)
[ Info: [ 78%] LOSS: training ≈ 0.246  validation ≈ 0.2905 (118%)
[ Info: [ 78%] LOSS: training ≈ 0.246  validation ≈ 0.2905 (118%)
[ Info: [ 78%] LOSS: training ≈ 0.2459 validation ≈ 0.2905 (118%)
[ Info: [ 79%] LOSS: training ≈ 0.2459 validation ≈ 0.2905 (118%)
[ Info: [ 80%] LOSS: training ≈ 0.2459 validation ≈ 0.2905 (118%)
[ Info: [ 80%] LOSS: training ≈ 0.2458 validation ≈ 0.2905 (118%)
[ Info: [ 80%] LOSS: training ≈ 0.2458 validation ≈ 0.2905 (118%)
[ Info: [ 81%] LOSS: training ≈ 0.2458 validation ≈ 0.2905 (118%)
[ Info: [ 82%] LOSS: training ≈ 0.2457 validation ≈ 0.2905 (118%)
[ Info: [ 82%] LOSS: training ≈ 0.2457 validation ≈ 0.2905 (118%)
[ Info: [ 82%] LOSS: training ≈ 0.2457 validation ≈ 0.2905 (118%)
[ Info: [ 83%] LOSS: training ≈ 0.2456 validation ≈ 0.2905 (118%)
[ Info: [ 84%] LOSS: training ≈ 0.2456 validation ≈ 0.2905 (118%)
[ Info: [ 84%] LOSS: training ≈ 0.2456 validation ≈ 0.2905 (118%)
[ Info: [ 84%] LOSS: training ≈ 0.2455 validation ≈ 0.2905 (118%)
[ Info: [ 85%] LOSS: training ≈ 0.2455 validation ≈ 0.2905 (118%)
[ Info: [ 86%] LOSS: training ≈ 0.2455 validation ≈ 0.2905 (118%)
[ Info: [ 86%] LOSS: training ≈ 0.2455 validation ≈ 0.2905 (118%)
[ Info: [ 86%] LOSS: training ≈ 0.2454 validation ≈ 0.2905 (118%)
[ Info: [ 87%] LOSS: training ≈ 0.2454 validation ≈ 0.2905 (118%)
[ Info: [ 88%] LOSS: training ≈ 0.2454 validation ≈ 0.2905 (118%)
[ Info: [ 88%] LOSS: training ≈ 0.2453 validation ≈ 0.2905 (118%)
[ Info: [ 88%] LOSS: training ≈ 0.2453 validation ≈ 0.2905 (118%)
[ Info: [ 89%] LOSS: training ≈ 0.2453 validation ≈ 0.2905 (118%)
[ Info: [ 90%] LOSS: training ≈ 0.2453 validation ≈ 0.2905 (118%)
[ Info: [ 90%] LOSS: training ≈ 0.2452 validation ≈ 0.2905 (118%)
[ Info: [ 90%] LOSS: training ≈ 0.2452 validation ≈ 0.2905 (118%)
[ Info: [ 91%] LOSS: training ≈ 0.2452 validation ≈ 0.2905 (118%)
[ Info: [ 92%] LOSS: training ≈ 0.2452 validation ≈ 0.2905 (118%)
[ Info: [ 92%] LOSS: training ≈ 0.2451 validation ≈ 0.2905 (118%)
[ Info: [ 92%] LOSS: training ≈ 0.2451 validation ≈ 0.2905 (119%)
[ Info: [ 93%] LOSS: training ≈ 0.2451 validation ≈ 0.2905 (119%)
[ Info: [ 94%] LOSS: training ≈ 0.2451 validation ≈ 0.2905 (119%)
[ Info: [ 94%] LOSS: training ≈ 0.2451 validation ≈ 0.2905 (119%)
[ Info: [ 94%] LOSS: training ≈ 0.245  validation ≈ 0.2905 (119%)
[ Info: [ 95%] LOSS: training ≈ 0.245  validation ≈ 0.2905 (119%)
[ Info: [ 96%] LOSS: training ≈ 0.245  validation ≈ 0.2905 (119%)
[ Info: [ 96%] LOSS: training ≈ 0.245  validation ≈ 0.2905 (119%)
[ Info: [ 96%] LOSS: training ≈ 0.2449 validation ≈ 0.2905 (119%)
[ Info: [ 97%] LOSS: training ≈ 0.2449 validation ≈ 0.2905 (119%)
[ Info: [ 98%] LOSS: training ≈ 0.2449 validation ≈ 0.2905 (119%)
[ Info: [ 98%] LOSS: training ≈ 0.2449 validation ≈ 0.2905 (119%)
[ Info: [ 98%] LOSS: training ≈ 0.2449 validation ≈ 0.2905 (119%)
[ Info: [ 99%] LOSS: training ≈ 0.2448 validation ≈ 0.2905 (119%)
[ Info: [100%] LOSS: training ≈ 0.2448 validation ≈ 0.2905 (119%)
[ Info: [100%] LOSS: training ≈ 0.2448 validation ≈ 0.2905 (119%)
[ Info: [  0%] LOSS: training ≈ 0.4215
[ Info: [  1%] LOSS: training ≈ 0.3806
[ Info: [  2%] LOSS: training ≈ 0.3564
[ Info: [  2%] LOSS: training ≈ 0.3399
[ Info: [  2%] LOSS: training ≈ 0.3279
[ Info: [  3%] LOSS: training ≈ 0.3185
[ Info: [  4%] LOSS: training ≈ 0.311 
[ Info: [  4%] LOSS: training ≈ 0.3048
[ Info: [  4%] LOSS: training ≈ 0.2996
[ Info: [  5%] LOSS: training ≈ 0.2952
[ Info: [  6%] LOSS: training ≈ 0.2914
[ Info: [  6%] LOSS: training ≈ 0.2881
[ Info: [  6%] LOSS: training ≈ 0.2852
[ Info: [  7%] LOSS: training ≈ 0.2826
[ Info: [  8%] LOSS: training ≈ 0.2802
[ Info: [  8%] LOSS: training ≈ 0.2782
[ Info: [  8%] LOSS: training ≈ 0.2763
[ Info: [  9%] LOSS: training ≈ 0.2746
[ Info: [ 10%] LOSS: training ≈ 0.2731
[ Info: [ 10%] LOSS: training ≈ 0.2717
[ Info: [ 10%] LOSS: training ≈ 0.2704
[ Info: [ 11%] LOSS: training ≈ 0.2692
[ Info: [ 12%] LOSS: training ≈ 0.2681
[ Info: [ 12%] LOSS: training ≈ 0.2671
[ Info: [ 12%] LOSS: training ≈ 0.2662
[ Info: [ 13%] LOSS: training ≈ 0.2654
[ Info: [ 14%] LOSS: training ≈ 0.2646
[ Info: [ 14%] LOSS: training ≈ 0.2639
[ Info: [ 14%] LOSS: training ≈ 0.2632
[ Info: [ 15%] LOSS: training ≈ 0.2626
[ Info: [ 16%] LOSS: training ≈ 0.262 
[ Info: [ 16%] LOSS: training ≈ 0.2614
[ Info: [ 16%] LOSS: training ≈ 0.2609
[ Info: [ 17%] LOSS: training ≈ 0.2605
[ Info: [ 18%] LOSS: training ≈ 0.26  
[ Info: [ 18%] LOSS: training ≈ 0.2596
[ Info: [ 18%] LOSS: training ≈ 0.2592
[ Info: [ 19%] LOSS: training ≈ 0.2589
[ Info: [ 20%] LOSS: training ≈ 0.2585
[ Info: [ 20%] LOSS: training ≈ 0.2582
[ Info: [ 20%] LOSS: training ≈ 0.2579
[ Info: [ 21%] LOSS: training ≈ 0.2576
[ Info: [ 22%] LOSS: training ≈ 0.2573
[ Info: [ 22%] LOSS: training ≈ 0.2571
[ Info: [ 22%] LOSS: training ≈ 0.2568
[ Info: [ 23%] LOSS: training ≈ 0.2566
[ Info: [ 24%] LOSS: training ≈ 0.2564
[ Info: [ 24%] LOSS: training ≈ 0.2562
[ Info: [ 24%] LOSS: training ≈ 0.256 
[ Info: [ 25%] LOSS: training ≈ 0.2558
[ Info: [ 26%] LOSS: training ≈ 0.2557
[ Info: [ 26%] LOSS: training ≈ 0.2555
[ Info: [ 26%] LOSS: training ≈ 0.2554
[ Info: [ 27%] LOSS: training ≈ 0.2552
[ Info: [ 28%] LOSS: training ≈ 0.2551
[ Info: [ 28%] LOSS: training ≈ 0.255 
[ Info: [ 28%] LOSS: training ≈ 0.2548
[ Info: [ 29%] LOSS: training ≈ 0.2547
[ Info: [ 30%] LOSS: training ≈ 0.2546
[ Info: [ 30%] LOSS: training ≈ 0.2545
[ Info: [ 30%] LOSS: training ≈ 0.2544
[ Info: [ 31%] LOSS: training ≈ 0.2543
[ Info: [ 32%] LOSS: training ≈ 0.2542
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 33%] LOSS: training ≈ 0.254 
[ Info: [ 34%] LOSS: training ≈ 0.2539
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 35%] LOSS: training ≈ 0.2537
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2535
[ Info: [ 37%] LOSS: training ≈ 0.2535
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2533
[ Info: [ 39%] LOSS: training ≈ 0.2533
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 41%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.253 
[ Info: [ 43%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 45%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 47%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 49%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 51%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 53%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 59%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 61%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 63%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 65%] LOSS: training ≈ 0.2524
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 67%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 69%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 71%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 73%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 75%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 77%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2522
[ Info: [ 79%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 81%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 83%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 85%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 87%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 89%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 91%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 93%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 95%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 97%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 99%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
Test Summary: | Pass  Total      Time
Package       |  301    301  21m36.9s
     Testing SDeMo tests passed 

Testing completed after 1351.16s

PkgEval succeeded after 1415.86s